Construction of large-scale global minimum concave quadratic test problems
Journal of Optimization Theory and Applications
A collection of test problems for constrained global optimization algorithms
A collection of test problems for constrained global optimization algorithms
Randomly Generated Test Problems for Positive Definite Quadratic Programming
ACM Transactions on Mathematical Software (TOMS)
Algorithm 728: FORTRAN subroutines for generating quadratic bilevel programming test problems
ACM Transactions on Mathematical Software (TOMS)
Computational Optimization and Applications - Special issue on computational optimization—a tribute to Olvi Mangasarian, part II
Parallel Implementation of Successive Convex Relaxation Methods for Quadratic Optimization Problems
Journal of Global Optimization
A Trust-Region Method for Nonlinear Bilevel Programming: Algorithm and Computational Experience
Computational Optimization and Applications
Global solution of bilevel programs with a nonconvex inner program
Journal of Global Optimization
Solving Bilevel Multi-Objective Optimization Problems Using Evolutionary Algorithms
EMO '09 Proceedings of the 5th International Conference on Evolutionary Multi-Criterion Optimization
Constructing test problems for bilevel evolutionary multi-objective optimization
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
On computational search for optimistic solutions in bilevel problems
Journal of Global Optimization
Bilevel multi-objective optimization problem solving using progressively interactive EMO
EMO'11 Proceedings of the 6th international conference on Evolutionary multi-criterion optimization
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This paper describes a technique for generating sparse or dense quadratic bilevel programming problems with a selectable number of known global and local solutions. The technique described here does not require the solution of any subproblems. In addition, since most techniques for solving these problems begin by solving the corresponding relaxed quadratic program, the global solutions are constructed to be different than the global solution of this relaxed problem in a selectable number of upper- and lower-level variables. Finally, the problems that are generated satisfy the requirements imposed by all of the solution techniques known to the authors.